A bi-level evolutionary optimization approach for integrated production and transportation scheduling

The integrated scheduling problem is formulated as a bi-level mixed-integer nonlinear program.Consider unrelated parallel-machine environment and product batch-based delivery.An evolution-strategy-based bi-level evolutionary approach is developed.The proposed approach is superior to other 3 intelligent algorithms-based approaches. This paper investigates an integrated production and transportation scheduling (IPTS) problem which is formulated as a bi-level mixed integer nonlinear program. This problem considers distinct realistic features widely existing in make-to-order supply chains, namely unrelated parallel-machine production environment and product batch-based delivery. An evolution-strategy-based bi-level evolutionary optimization approach is developed to handle the IPTS problem by integrating a memetic algorithm and heuristic rules. The efficiency and effectiveness of the proposed approach is evaluated by numerical experiments based on industrial data and industrial-size problems. Experimental results demonstrate that the proposed approach can effectively solve the problem investigated.

[1]  Per Kristian Lehre,et al.  The generalized minimum spanning tree problem: a parameterized complexity analysis of bi-level optimisation , 2013, GECCO '13.

[2]  Vinícius Amaral Armentano,et al.  Tabu search with path relinking for an integrated production-distribution problem , 2011, Comput. Oper. Res..

[3]  Supachai Pathumnakul,et al.  An interactive approach to optimize production–distribution planning for an integrated feed swinecompany , 2013 .

[4]  Zhi-Long Chen,et al.  Integrated Production and Outbound Distribution Scheduling: Review and Extensions , 2010, Oper. Res..

[5]  Felix T.S. Chan,et al.  Integration of manufacturing and distribution networks in a global car company – network models and numerical simulation , 2011 .

[6]  Seyed Jafar Sadjadi,et al.  A probabilistic bi-level linear multi-objective programming problem to supply chain planning , 2007, Appl. Math. Comput..

[7]  Suh-Jenq Yang,et al.  Decision support for unrelated parallel machine scheduling with discrete controllable processing times , 2015, Appl. Soft Comput..

[8]  George L. Vairaktarakis,et al.  Integrated Scheduling of Production and Distribution Operations , 2005, Manag. Sci..

[9]  Chuan-Kang Ting,et al.  The selective pickup and delivery problem: Formulation and a memetic algorithm , 2013 .

[10]  S.Y.S. Leung,et al.  A hybrid intelligent model for order allocation planning in make-to-order manufacturing , 2013, Appl. Soft Comput..

[11]  Bilge Bilgen,et al.  Integrated production scheduling and distribution planning in dairy supply chain by hybrid modelling , 2013, Ann. Oper. Res..

[12]  Fevrier Valdez.  Bio-Inspired Optimization Methods , 2015, Handbook of Computational Intelligence.

[13]  Kathryn E. Stecke,et al.  Production and Transportation Integration for a Make-to-Order Manufacturing Company with a Commit-to-Delivery Business Mode , 2007, Manuf. Serv. Oper. Manag..

[14]  Seyed Hessameddin Zegordi,et al.  Integrating production and transportation scheduling in a two-stage supply chain considering order assignment , 2009 .

[15]  Milind Dawande,et al.  Supply Chain Scheduling: Distribution Systems , 2006 .

[16]  Carlos Cotta,et al.  Memetic algorithms and memetic computing optimization: A literature review , 2012, Swarm Evol. Comput..

[17]  Oscar Castillo,et al.  Modification of the Bat Algorithm Using Type-2 Fuzzy Logic for Dynamical Parameter Adaptation , 2017, Nature-Inspired Design of Hybrid Intelligent Systems.

[18]  Sigrid Knust,et al.  Integrated production and distribution scheduling with lifespan constraints , 2012, Annals of Operations Research.

[19]  Mir Saman Pishvaee,et al.  A memetic algorithm for bi-objective integrated forward/reverse logistics network design , 2010, Comput. Oper. Res..

[20]  Yeu-Ruey Tzeng,et al.  A new heuristic based on local best solution for permutation flow shop scheduling , 2015, Appl. Soft Comput..

[21]  Gregor Papa,et al.  Metaheuristic approach to transportation scheduling in emergency situations , 2013 .

[22]  John H. Holland,et al.  Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .

[23]  Zukui Li,et al.  Integrated production planning and scheduling using a decomposition framework , 2009 .

[24]  Wing-Keung Wong,et al.  Optimizing decision making in the apparel supply chain using artificial intelligence (AI): From production to retail , 2013 .

[25]  Mostafa Hajiaghaei-Keshteli,et al.  Solving the integrated scheduling of production and rail transportation problem by Keshtel algorithm , 2014, Appl. Soft Comput..

[26]  J. Bard.  Some properties of the bilevel programming problem , 1991 .

[27]  Ching-Jong Liao,et al.  Integrating production and transportation scheduling in a two-stage supply chain , 2015 .

[28]  Scott J. Mason,et al.  Multi-objective analysis of an integrated supply chain scheduling problem , 2012 .

[29]  Christian A. Ullrich.  Integrated machine scheduling and vehicle routing with time windows , 2013, Eur. J. Oper. Res..

[30]  Pablo Moscato,et al.  On Evolution, Search, Optimization, Genetic Algorithms and Martial Arts : Towards Memetic Algorithms , 1989 .

[31]  Charles E. Blair,et al.  Computational Difficulties of Bilevel Linear Programming , 1990, Oper. Res..

[32]  Seyed Hessameddin Zegordi,et al.  A novel genetic algorithm for solving production and transportation scheduling in a two-stage supply chain , 2010, Comput. Ind. Eng..

[33]  Chung-Yee Lee,et al.  Machine scheduling with job delivery coordination , 2004, Eur. J. Oper. Res..

[34]  Hao Huang,et al.  Hybrid real-coded genetic algorithm for data partitioning in multi-round load distribution and scheduling in heterogeneous systems , 2014, Appl. Soft Comput..

[35]  Oscar Castillo,et al.  A survey on nature-inspired optimization algorithms with fuzzy logic for dynamic parameter adaptation , 2014, Expert Syst. Appl..

[36]  H. Neil Geismar,et al.  The Integrated Production and Transportation Scheduling Problem for a Product with a Short Lifespan , 2008, INFORMS J. Comput..

[37]  Chung Yee Lee,et al.  Production and transport logistics scheduling with two transport mode choices , 2005 .

[38]  Michael R. Bussieck,et al.  MINLP Solver Software , 2011 .

[39]  A. Dickson.  On Evolution , 1884, Science.

[40]  Patrice Marcotte,et al.  Bilevel programming: A survey , 2005, 4OR.

[41]  Hans-Paul Schwefel,et al.  Evolution strategies – A comprehensive introduction , 2002, Natural Computing.

[42]  Oscar Castillo,et al.  Modification of the Bat Algorithm using fuzzy logic for dynamical parameter adaptation , 2015, 2015 IEEE Congress on Evolutionary Computation (CEC).

[43]  Xin Yao,et al.  Mathematical modeling and multi-objective evolutionary algorithms applied to dynamic flexible job shop scheduling problems , 2015, Inf. Sci..

[44]  Lin Lin,et al.  Multiobjective evolutionary algorithm for manufacturing scheduling problems: state-of-the-art survey , 2014, J. Intell. Manuf..